Benchmarking

Benchmark suite for Autoregressive Neural Emulators of PDEs in JAX.

OpenMMLab Image and Video Editing Toolbox and Benchmark

A framework for benchmarking causal inference.

Benchmarking library for generative algorithms

A Flexible Framework for Accelerating LLMs Benchmarking

A library for benchmarking AI models

SyntheRela - Synthetic Relational Data Generation Benchmark

mcsm-benchs: A benchmarking toolbox for Multi-Component Signal Methods.

Rotation Detection Toolbox and Benchmark

TabularBench: Adversarial robustness benchmark for tabular data

Fuzzy Data Benchmark

GitLab Security Compliance CLI

Code to benchmark and evaluate MLLM on industrial data (data itself are not part of the publication).

Benchmark PDF extraction tools for use with RAG applications

The companion code for the FanOutQA dataset + benchmark for LLMs.

MESS – Multi-domain Evaluation of Semantic Segmentation

GuardBench: A Large-Scale Benchmark for Guardrail Models

Table Retrieval for Generative Tasks Benchmark

ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction

Advanced Disk Benchmark Tool

A simple benchmarking library

I/O profiler for deep learning python apps. Specifically for dlio_benchmark.

MedSegBench: A Comprehensive Benchmark for Medical Image Segmentation in Diverse Data Modalities

Interactive Benchmarking for Machine Learning.

The benchmark package allows you to test AI Brain

This repository is designed to simplify the evaluation process of vision-language models. It provides a comprehensive set of tools and scripts for evaluating VLM models and benchmarks.

a python package to benchmarks algorithms against various datasets

A simple ANN benchmark tools

Experiment management and benchmark tools for mathematical optimization

Use LLMs to get classification risk scores on tabular tasks.

Python package for building, simulating, and benchmarking hybrid quantum-classical algorithms.

A Comprehensive Benchmark of Deep Model Fusion

Superseded by: gbd-tools

LLM semantic testing and benchmarking framework

UNIQUE is a Python package for benchmarking uncertainty estimation and quantification methods for Machine Learning models predictions.

SpuCo: Spurious Correlations Datasets and Benchmarks

Easily generate simple continual learning benchmarks.

Pluristic alignment evaluation benchmark for LLMs

Benchmarks for Bayesian optimization

BrowserGym integration for the WebLINX benchmark

Electrical Power System Benchmark Models.

Benchmark Tool for CaddoBenchmark Project

a Python package for automatic training and benchmarking of Language Models.

CLI extension for AEA framework benchmarking.

Vision Document Retrieval (ViDoRe): Benchmark. Evaluation code for the ColPali paper.

Benchmarking tool for vector databases

AI Maintainer Agent Harness for our benchmarking and Marketplace API and platform

A benchmarking sandbox for mode choice models

Bayesian optimization benchmark system

Simple probabilistic time series benchmark models